Concurrent Enrollment's Effect on Remedial and General Education Math

The Effectiveness of Concurrent Enrollment
in Remedial Mathematics and General
Education Level Mathematics
By
Ryan Edward Grossman
B.S. (Mathematics & Mathematics Education), Indiana State University, 2010
Advisor: Dr. Subhash Bagui
A Graduate Proseminar
In Partial Fulfillment of the Degree of
Master of Science in Mathematical Sciences
The University of West Florida
July 2013

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The Proseminar of Ryan Edward Grossman is approved:
________________________________________ _______________
Subhash Bagui, Ph.D., Proseminar Advisor Date
_________________________________________ _______________
Josaphat Uvah, Ph.D., Proseminar Committee Chair Date
Accepted for the Department:
________________________________________ _______________
Jaromy Kuhl, Ph.D., Chair Date

iii
ABSTRACT
This study focuses on the development and implementation of the co-requisite model
implemented at Midwest Community College. The main research question is whether or not
concurrent enrollment in remediation has a statistically significant impact on student success in
the general education level math. Students were selected for the co-requisite program on the
basis of their major and initial willingness to invest a significant amount of time studying
mathematics. This ex post facto study investigates relationships between students enrolled in the
general education mathematics course and the concurrent tutorial class and those not in the
tutorial class and their overall success in the general education mathematics course. The data
analysis shows that students enrolled in the tutorial class are statistically indistinguishable from
those not enrolled in the tutorial class. Of the tutorial students who completed the general
education class, the general education mathematics class pass rate was 83%, a dramatic
improvement over the pass rate of those not enrolled in the tutorial class. Future research will
focus on variations of the concurrent enrollment model and how those changes affect student
success rates.

iv
DISCLOSURES
Midwestern Community College, the investigator’s employer, utilized the COMPASS
Placement Exam written by ACT, Inc during the course of this study. The investigator is an
independent contractor for ACT, Inc. who writes test questions for various ACT assessments.
After the investigator finished data collection, the College switched to a new placement exam.
The investigator played no role in the decision to retain or release the services of ACT, Inc. in
regards to College’s use of their placement exam services.
As disclosed on the paperwork for the Institutional Review Board, the instructor of the
tutorial class is the same person as the author of this study. During all phases of the study, the
protocols set forth by the Institutional Review Board approval were followed. Student
participation in this study was completely optional. Participation or the lack thereof did not
impact the grade the student received in either the general education class or the tutorial class.

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ACKNOWLEDGEMENTS
The investigator would like to thank the numerous people involved with this project.
First, I would like to thank my Proseminar advisor, Dr. Bagui. I appreciate his willingness to
coach me through the development of the Proseminar and to instruct me on the fundamentals of
Mathematical Statistics. I also am thankful for the editing services provided by Dr. Hemasinha.
His comments provided me with great insight into improving my Proseminar and Matrix Theory
work.
I would like to express my gratitude to the entire faculty in the Mathematics and Statistics
Department at University of West Florida. Even though I have not worked with everyone, I am
indebted with the quality of instruction offered to me. I especially would like to thank Dr. Li for
setting me on the track to success and for Dr. Kuhl for ensuring my completion.
Next, I would like to thank the students, faculty and staff at Midwestern Community
College for permitting me this opportunity to improve the quality of instruction at our institution.
Without the explicit support of Carrie McCammon, my department chair, Rae Lynn Prouse,
Assistant Registrar, Darla Crist, Writing Center Director, and the students involved with this
study, this project would not be possible.
While no funding originated from my employer or University of West Florida for this
research endeavor, I would like to extend my gratitude to both higher education entities for their
continued support. I appreciate Midwestern Community College’s tuition assistance and the
staff in the Human Resources Office for supporting me in my educational pursuits. The
investigator also thanks the University of West Florida’s Department of Mathematics and
Statistics for sharing their scholarship funding with me.

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Finally, I wish to recognize my family. I am forever grateful for the unconditional
support my family showed me, especially my wife, Tiffany. She made an untold number of
sacrifices in the name of my success. Without her I could not have finished my Master’s degree.

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TABLE OF CONTENTS
Page
TITLE PAGE....................................................................................................................... i
APPROVAL PAGE............................................................................................................ ii
ABSTRACT....................................................................................................................... iii
DISCLOSURES................................................................................................................. iv
ACKNOWLEDGEMENTS.................................................................................................v
TABLE OF CONTENTS.................................................................................................. vii
CHAPTER I. INTRODUCTION.........................................................................................1
A. Statement of Problem..........................................................................................1
B. Relevance of Problem .........................................................................................2
C. Literature Review................................................................................................3
1. Relational versus Instrumental Understanding...............................................3
2. Ohio University’s Remote Learning Experiment ...........................................3
3. Revamping Virginia Tech’s Mathematics Curriculum...................................5
4. Tennessee Board of Regents’ Developmental Education Transformation.....6
5. National Redesign Efforts...............................................................................7
D. Limitations ..........................................................................................................8
CHAPTER II. INSTRUCTIONAL MODEL ....................................................................10
A. Assumptions of the Model................................................................................10
B. Student Performance Assessment Methodology...............................................12
C. Description of Statistical Tests..........................................................................15
1. Mann-Whitney U ..........................................................................................15
2. Chi-Square ....................................................................................................16
3. Pearson Correlations.....................................................................................16
4. Linear Regression .........................................................................................17
D. Statistical Testing and Analysis ........................................................................18
CHAPTER III. CONCLUSIONS ......................................................................................23
A. Summary: Interpretation ...................................................................................23
B. Suggestions for Further Study.......................................................................... 24
REFERENCES ..................................................................................................................27

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APPENDICES ...................................................................................................................30
A. IRB Approval....................................................................................................30
B. Syllabi................................................................................................................32
C. Attitude Survey Data.........................................................................................58
D. SPSS Output......................................................................................................64

1
Chapter I-INTRODUCTION
A. Statement of Problem
The community college used in this study is one of the largest college systems in the Midwest with a total
system-wide headcount of 174,806 for the 2010-2011 school year [10, 19]. In an era where more college graduates are
needed, the state government applies great pressure upon Midwestern Community College, and other institutions of
higher learning, to produce more highly qualified graduates in a timely manner by tying a growing portion of the
college’s funding to persistence, degree completion and remediation completion rates [20]. In response to this
demand, the college administration identified several bottleneck factors preventing students from graduating and
persisting: poor success rates in remedial and general education mathematics courses were an immense culprit in this
regard [1].
The author’s home mathematics department faced an extraordinarily high failure rate in remedial and general
education mathematics courses, 56.1% and 41.2% respectively, for the 2010-2011 academic year1
. This was not a new
problem; the department routinely faced high failure rates for several semesters prior to the 2010-2011 academic
year. Traditionally, students who need remediation complete a semester (or more) of remedial mathematics course
work, followed by college-level mathematics. A majority of the college’s students need one general education
mathematics course that focuses more on common usages of mathematics and less on the algebra called “Concepts in
Mathematics.” The percent of students who satisfactorily completed the “Concepts in Mathematics” course, much less
completed the remedial mathematics course(s) prior to this general education course, needs significant improvement
because only 54%1
of students passed in the Fall 2011 semester. Of those students that started in remedial
mathematics, only about 6%1
passed a college-level mathematics course. To remedy this problem, the department
decided to adopt the co-requisite enrollment model, which takes students who would otherwise not be eligible to
1
Figures calculated by investigator using data archived by mathematics department. This only includes Fall 2010 and Spring 2011
semesters.

2
attempt the general education math course and concurrently enrolls them into a tutorial class. The reasons the
mathematics department selected the co-requisite model are:
 The co-requisite model condenses all of the math requirements into one semester instead of multiple
semesters.
 Students receive assistance just-in-time. In addition, the faculty did not try to fill in all of the gaps of
the students’ knowledge base, just what was needed to be successful in the general education level
mathematics course.
This approach to remedial mathematics is in stark contrast to the status quo of remediating students before they
would be permitted to enroll in the mathematics course needed for their degree. The main research question is
whether or not concurrent enrollment in remediation has a statistically significant impact on student success in the
general education level math?
B. Relevance of Problem
Mathematics is often thought of as a “gatekeeper” course: a course that prevents students from completing
their degree. Academic programs with high student interest and demanding academic rigor often require rigorous
mathematics courses as filters for students who want to enter into their programs but cannot handle the demands of
those programs: “‘Remedial math has become the largest single barrier to student advancement’“ [12]. Mathematics
courses also act as an unintentional barrier for students who need at least one mathematics course to graduate.
According to Complete College America, 46.4% of incoming students at Midwestern Community College need
remediation in mathematics. Of those students who enroll in at least one remediation class, only 63.7% complete the
remediation program and 9.2% of those that complete remediation graduate with an associate’s degree within 3 years
[3].
Students enrolled in any remedial course (reading, writing or mathematics) must earn a C or better in order to
move onto the next course per college policy. Statewide, the college’s success rates in remedial mathematics are

3
dismal at best. In the 2010-2011 academic year, 52.6% of all students enrolled in a remedial mathematics course
passed in contrast to the target of 58%. The pass rate only improved two percentage points for the 2011-2012
academic year but did not keep up with the targeted pass rate of 62% [11]. The poor pass rates are frustrating the
college’s efforts to increase graduation and persistence rates as one of the pre-requisites to other non-math intensive
classes is that students completed the remedial math sequence (or tested out of remedial mathematics).
C. Literature Review
1. Relational versus Instrumental Understanding.
Before any discussion on successful instructional methods begins, types and degrees of understanding in
mathematics need to be discerned. The most commonly accepted “types” of understanding in mathematics are
“relational understanding” and “instrumental understanding” as advocated by Skemp [18]. Relational understanding
encompasses comprehension in both the how and why in mathematical phenomenon, whereas instrumental is just the
how; thus, the student with instrumental understanding is being used like an apparatus in a larger process that can be
easily replaced. Society and educators must be careful not to mismatch the instrumental educator with the student
who yearns for relational understanding and vice versa; great time and resources have been and will be wasted
because of this mismatch [18]. Skemp’s article [18] is relevant to the larger scope of this literature review as it
establishes goals and guidelines to which a mathematics educator should strive to obtain: the relationally taught
student is the self-reliant and self-curious student who will perform better in mathematics classes presently and in the
future. Furthermore, the students who enter the co-requisite enrollment program are more likely to be instrumentally
driven. This group of students is ultimately only interested in the pre-requisite concepts and skills needed to be
successful in the college-level course and nothing more.
2. Ohio University’s Remote Learning Experiment.
One of the grandiose questions educational researchers hope to answer is “Is there one (or multiple)
methodologies that work best for certain subjects?” While there is no definitive answer as of yet, the educational

4
community is on track to answering the question “What are effective methodologies for any discipline?” Remote
learning (now often called distance learning or e-learning) was the subject of study at Ohio University for their remedial
mathematics class. Can remote learning be an effective and efficient tool to teach remedial mathematics?
Lopez, Permouth and Keck [16] studied three sections of Math 101 at Ohio University for a particular semester
and varied the attendance policies in each of the three sections where each section had only 20 students. The first
section had mandatory attendance policies. Students in the second section were required to attend at least two days a
week (one for testing and the other for lecture). The third section only stipulated students to attend one day a week
(for testing only). Normally, Math 101 meets three days a week plus an additional day for testing. This quasi-
experimental, repeated measures design kept all other factors constant across all sections: same assessments, same
lecture content, same deadlines, same grading scale. The hypotheses were freedom of choice would direct students
towards remote learning and attendance is positively correlated to class performance. The researchers failed to reject
both null hypotheses; however, they did affirm weaker students are better suited with classes with strict guidelines
and policies. Based upon their review of institutional data, both the remote and traditional sections were consistent
with the average scores on the final exams of years past [16].
While this study has internal validity concerns (testing, selection, small sample size), the conclusion finds that
no adverse conditions were found for students enrolled in the remote learning section. For those students who are
disciplined enough to move through a course with relatively little guidance or pushing from the instructor, they are to
generally do well in the online (or remote) environment. Unfortunately, most remedial students cannot handle such
freedom and responsibility on their own [16]. This conclusion is also supported by a similar study conducted by Li,
Uvah, Amin and Hemasinha [15]because their study showed the success rates for students in a purely online format for
College Algebra was significantly worse than those in face-to-face sections. They varied the instructional format
(purely online; face-to-face with instructional technology inclusion and face-to-face without any instructional
technology) of College Algebra and kept the other factors constant. Even though the Mathematics and Statistics
Department at the University of West Florida did not alter the attendance policies as Ohio University did, they note

5
“maturity and self-discipline” along with “ill-preparedness” are factors that contributed to the poor pass rates in the
purely online section of College Algebra [15].
3. Revamping Virginia Tech’s Mathematics Curriculum.
Virginia Tech was one of the first schools to redesign their mathematics curriculum in light of pathetic student
success rates and ever declining financial support from state government. Greenburg and Williams, mathematics
faculty at Virginia Tech, outline the development of their “Math Emporium” and the reasons for their high success
rates across the undergraduate curriculum. The Math Department at Virginia Tech obtained an abandoned
department store to house five hundred fifty computer work stations for students to complete their course activities
twenty-four hours a day, with instructional staff available fourteen hours a day. Most of the course activities can be
completed anywhere the student has internet access; however, instructional staff proctored all high-stakes
assessments at the Math Emporium. Students prepared for their high-stakes assessments by reading an online text or
watching videos uploaded to the Internet and completing online homework and quizzes. Any time students needed
assistance at the Math Emporium, they flagged down a near-by instructional staff member. The pool of questions used
for homework and quizzes was the same pool of algorithmic questions used for the high-stakes assessments. The
deliberate use of the same pool of questions for all course activities encouraged mastery learning; students knew
simply rehearsing solutions from previous assignments would not be satisfactory to passing the course [9].
The benefits to this approach are numerous, according to the authors. Virginia Tech students witnessed:
greater autonomy in completing course activities; enhanced time management skills; and, improved classroom
performance in future mathematics courses. The faculty and administration of Virginia Tech produced significant cost
savings; streamlined processes and resources; and, achieved economies-of-scale. They continuously search for new
ways to improve student success and lower the cost of instruction [9].

6
4. Tennessee Board of Regents’ Developmental Education Transformation.
The institutions of higher education in Tennessee faced a disproportionate amount of enrollment in
developmental education courses with low success rates. The Tennessee Board of Regents (TBR) received a grant to
develop new models of learning to improve retention rates and simultaneously reduce the instructional costs such that
the models were replicable and scalable across the curriculum. Berryman and Short [2], members of the Tennessee
Board of Regents, oversaw the transformation in developmental mathematics courses, although the grant was aimed
at improving all aspects of developmental education.
Jackson State Community College created their own textbook, assignments and assessments using an online
homework management system in an emporium style similar to Virginia Tech’s model. Instead of starting at the very
beginning of a course, a student starts and stops based on what competencies that student’s major department deems
appropriate and the student’s mathematics scores on the placement assessment. Only 18% of the academic programs
at Jackson State required all competencies to be met in order to be successful in college-level coursework [2].
Cleveland State Community College used a similar design of creating competencies and only requiring students to
master the competencies needed for his or her academic program; however, the faculty at Cleveland State created
their own video lectures that were inserted into the online homework management system. This freed the faculty to
spend more one-on-one time with each student and to teach more than their previous norm of five sections [2].
The benefits of these two redesigns are notable. Jackson State experienced a twenty percent decrease in the
cost-per-student ratio, from $177 to $141. Cleveland State’s reduction in overall instructional costs saved the
institution $51,000 (19% reduction in instructional costs). More impressive is Cleveland State’s increase in the success
rate from 54% to 72% [2]. The most impressive statistic is when Cleveland State compared the students who entered
college-level mathematics using the traditional lecture model versus the emporium model. The math faculty found
that “33% more students passed the next college-level math course after having completed the redesigned
developmental math course when compared with students who went through the traditional approach to
remediation” [2].

7
Another notable Tennessee redesign originates from Austin Peay State University. Instead of requiring
students to advance through a remedial course sequence and then onto their college level mathematics course(s),
students who qualified for remedial classes are enrolled into the college level mathematics course and a concurrent
“linked workshop” where a successful mathematics student who attended the same section as the workshop students
would each workshop students pre-requisite skills, provide peer tutoring to all workshop students and review for tests.
All of this extra scaffolding occurs in the background of the college level course as the professor would progress with
the course as s/he normally would. Of those students who qualified for remediation, the success rates improved for
the Elements of Statistics class from 23% to 54% and a more dramatic improvement in their liberal arts survey course
from 33% to 71% [4].
5. National Redesign Efforts.
The need to redesign remedial courses is not unique to any particular state. The mission of The National Center
for Academic Transformation (NCAT) is to “improve student learning outcomes and reduce the cost of higher
education” using information technology. NCAT works with institutions to achieve this lofty mission by researching ,
giving access to research-based solutions and increasing access to and employing institutional assets more efficiently
[21]. Institutions are asked to “re-conceive” entire courses, not just select sections, to meet the objectives set forth in
NCAT’s mission statement. C. Twigg, the executive director of NCAT, developed four core principles NCAT lives by:
students spend most of their time “doing math problems” and not listening or watching someone else do them; the
amount of time spent on a type of problem is inversely proportional to the perceived level of difficultly; on-demand
assistance is provided to students when needed; and, doing math is obligatory [22].
Twigg [22] continues her discussion of redesign by highlighting four-year and two-year institutions successes
and lessons learned. Each institution modified the NCAT template to meet their unique needs. The common threads
between all of these institutions are the “Five Principles of Successful Course Redesign.” The entire course, from top to
bottom, must be deconstructed, critiqued and reassembled with new curriculum as needed. The focus of the course is
on the student’s learning; therefore, active learning is a necessity. Students cannot learn completely on their own, that

8
is why the instructional staff exists in the first place! Individualized assistance must be provided on-demand with
ongoing feedback from the instructional staff and the computer software. Finally, student successes and frustration
must be tracked to ensure student mastery [22].
D. Limitations
Several limitations exist within this study that impedes upon the generalization of its results. First, students
were hand-selected. The initial criteria used for enrollment into this program were:
 The student’s major only required this particular general education math course
 The student could devote a large portion of their time to studying math.
By nature of the scope and method of sample selection, the results of this study are not generalizable to the
other campuses of Midwestern Community College, much less any other institution of higher education. All of the
students used in this study called the author’s home campus their primary campus. Another factor for limiting the
generality of the results is the uniqueness of the tutorial class. No other campus of Midwestern Community College
taught the tutorial class in the same manner as the author did.
Another limitation to this study is the small sample size and the drop-out effect. The program started with a
total of thirteen enrolled students and ended with a total of ten enrolled students. The successes demonstrated by
this program should be taken with a grain of salt because of the limited pool of students used for this program. The
program experienced a large withdraw and failure to withdraw (FW) rate, in part due to the small number of enrolled
students and the frequency personal emergencies interrupted students’ coursework. Three students experienced life-
changing familial issues and two students gained or lost a job that directly impacted their studies. Maturity of students
should also be taken into consideration as Li, Uvah, Amin and Hemasinha [15] noted in their study of College Algebra
students.

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The final major limitation to this study was the frequent absence of the general education mathematics course
instructor, the department chair. She attended several meetings that conflicted with her class schedule; often the
meetings were not previously made known to her at the beginning of the semester as they should have been. While
she did provide students with out-of-class assignments when absent, that instructional time can never be made up. In
the instructor’s defense, she did offer optional review sessions on Fridays so her students could receive personalized
assistance from her.

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CHAPTER II-INSTRUCTIONAL MODEL
A. Assumptions of Instructional Model
The intent of the design of the program was to provide “just-in-time” assistance as in the cases of Virginia Tech
and Jacksonville State with the clear expectations of attendance and participation of Ohio University to enable
students to successfully pass their general education level mathematics class. To that end, the author and the
department chair expected students to attend and participate in both the tutorial class and the general education
math course on a regular basis. Even though students knew they would not directly receive credit towards their final
course grade because of attending either class, they were expected to come to class nevertheless. If a student missed
two consecutive class meetings of either the tutorial or the “Concepts in Mathematics” class, they received a phone
call or email alerting them to the instructor’s concerns using an online retention system. Both instructors could see
when either of them raised attendance or academic concerns on this system.
All students in the “Concepts in Mathematics” course were informed of and highly encouraged to utilize the
college’s tutoring services. It is not a course requirement of the college level course that students attend tutoring
sessions; students in the tutorial class, on the other hand, were expected to use a personal tutor on a regular basis. A
tutor from the tutoring center was set aside specifically for the students in the department chair’s “Concepts in
Mathematics” classes at specific times during the week and by appointment. Even though students from the tutorial
class were expected to obtain a tutor, the tutorial instructor could not award course credit for attending tutoring
sessions because of the tutoring center’s reluctance to release the names of students who were using their services.
The department chair and the author devised a pacing guide describing when topics would be taught in the
college-level course and what skills and concepts should be reviewed/taught in the tutorial class. Each class meeting
was seventy-five minutes in duration. Unlike the Austin Peay’s “Linked Workshop” model, this tutorial class had its
own homework assignments and a full-time instructor leading the class. The lecture component of the tutorial class

11
was kept to a maximum of twenty minutes. The remainder of the class time was used to answer student questions and
to work on their assignments from both the college level course and the tutorial course.
COMMENT: Students could not complete all of their work for one class during the tutorial class time alone.
This is why the department expects all students, regardless if they enrolled in remedial coursework or college level
coursework, to study at least three hours a week for each credit hour they were enrolled in outside of class. The
tutorial class and the “Concepts in Mathematics” class were three credits each, thus giving each student a total of
eighteen hours to spend outside of class studying. The department considers a student to be studying when they are
actively working with mathematics. This can come in many forms: working with a tutor or classmate, completing
homework, reading or watching online multimedia, etc.
So long as students were willing to invest the necessary time to study, it is the Math Department’s assumption
that any student who was willing to spend the requisite study time and utilize the College’s support structures could
pass the “Concepts in Mathematics” course. Both instructors maintained at least eight student office hours per week
and scheduled appointments outside of their normal office hours when necessary. Walk-in tutoring, in addition to
tutoring by appointment, was readily available to all students. The online homework system provided videos and other
learning assistance when the student needed them. The author stayed in close contact with the other instructor
throughout the semester, communicating student concerns and what topics should be reviewed or retaught in the
“Concepts in Mathematics” course. The bottom line is that both instructors were willing to, in the words of the
department chair, “bend over backwards” to be of assistance to the students.
Summary
 Remedial students can succeed in the “Concepts in Mathematics” class if they regularly attend the tutorial
class where they receive “just-in-time” assistance.
 All students can be successful if they take advantage of the tutoring and instructors’ office hours.
 Students were assigned homework and assessments in both classes.

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 The two instructors kept in close contact about student concerns and made themselves widely available for
student interaction outside of class.
B. Student Performance Assessment Methodology
The “Concepts in Mathematics” course has four main themes: probability, statistics, algebra and personal
finance, taught in this order. The reason for this particular ordering of topics was to give the tutorial students more
time to develop their algebra concepts and skills. All students in this general education mathematics class never
worked with Venn diagrams, counting rules, probability and statistics before, so this was a good place for all students
to start, especially since algebra was not a pre-requisite skill. The “Concepts in Mathematics” class contains four one
hundred point paper-pencil unit exams, regular online homework, and two online quizzes per unit, in-class
participation and a paper-pencil multiple choice final exam for a total of 600 points possible. The unit tests were taken
in-class whenever possible; otherwise, the tests were placed in the Testing Center where students were given a five
day window to complete the test. The class was given one bonus opportunity: if a student scored better on the final
exam than on the test with the lowest test score, the percentage the student earned on the final replaced the lowest
test score. Possible final course grades are A, B, C, D and F where the standard grading scale was used to calculate the
minimum number of points needed to earn a specific grade.
The department chair taught two sections of the general education math courses associated with this program;
the author taught the tutorial class. Students from the tutorial class enrolled in one of the department chair’s sections
of “Concepts in Mathematics” that met either before or after the tutorial class. The author coordinated with the other
instructor on a regular basis to address student and course concerns. If either instructor needed to modify what would
occur the next week, the circumstances and reasons were discussed.
The intent of the tutorial class structure was to give students the support they needed to be successful in their
college-level math course. To achieve that effect, the author designed the tutorial class so that students could express
their concerns at the beginning of class, then focus on the skills and concepts needed in the near future. The author
started class off by soliciting the students’ questions. Then, the author spent about twenty minutes discussing a skill or

13
concept the students needed in class in the near future; questions were entertained during this brief lecture period as
well. Finally, students were expected to complete homework and quizzes for the tutorial class using an online
homework management system. 200 points were possible for each unit test and 200 participation points for a total of
1200 points possible for the tutorial class. The standard grading scale was used as well; however, the grade students
earned in their tutorial class did not impact their grade point average but did impact their completion rate as
calculated by the Office of Financial Aid.
The homework and quiz structure inside of the tutorial class online homework system attempted to build upon
the students’ previous knowledge so they could focus on their deficiencies. Each unit had a proctored Pre-Test that all
students were required to attempt. The Pre-Test served one major purpose: to diagnose students’ strengths and
weaknesses. If a student scored 90% or better on the Pre-Test, then the student was excused from completing that
unit. A secondary purpose of the Pre-Test was to customize the students’ homework. If a student demonstrated
mastery of one particular topic on the Pre-Test, then they were excused from completing that type of problem on the
associated homework assignment(s). After completing the Pre-Test, students watched and engaged with the
multimedia. Students chose which multimedia activities they completed so long as they completed at least 70% of
each multimedia assignment. Next, the student would continue onto the homework for that unit. After completing all
of the homework and multimedia pairs in a unit, students could take the Practice Test for that Unit after the minimum
grade of 80% was earned on the homework assignments for that unit. The goal of the Practice Test was to prepare
students for their actual test, a required test review guide in another sense. The Practice Test simulated testing
conditions; students were allotted 90 minutes to complete the Practice Test and could not use notes (although the
Practice Test was not proctored). Finally, students attempted the Post-Test. Students were given 90 minutes to
complete the exam in the Testing Center using a calculator and scratch paper. The Pre-Test and Post-Test could only
be taken once; the multimedia and homework could be stopped and started as the student saw fit. The Final Exam for
the tutorial class consisted of students retaking the COMPASS Placement Exam. If a student completed all of their
units, the final exam was optional. If a student did not complete all of their units, the student was required to take the

14
exam. In either case, if the percent earned on the Final Exam was better than the student’s lowest scoring Post-Test
score, then the score earned on the Final Exam would replace that particular Post-Test score. The syllabi for both the
“Concepts in Mathematics” class and the tutorial class are included in the appendices.
There are a few more intricate details that distinguish this program from others similar to it. First, students
enrolled in this special program were given two scheduling options. They could go to the “Concepts in Mathematics”
course, then the tutorial class; or, students could attend the tutorial class first. Another important factor is regardless
of a student’s choice of which schedule he or she chose, a tutor was dedicated to this program. The tutor, a
mathematics major from a neighboring four-year institution, set aside time each week to work with students on a
walk-in basis. She was also available for appointments as well. Should a student not be able to work with this
particular tutor, the instructor and the author encouraged students to work with any other college tutor or to attend
an instructor’s review session. The author offered review sessions on demand if a student scheduled an appointment
in advance or during office hours. The hallmark portion of this design is that students learned the skills and concepts
necessary to be successful in the general-education level mathematics class when they needed it. This feature permits
students to focus on just the aspects of mathematics that are necessary to be successful in the general education math
class and not spend time on other topics not necessary to complete the “Concepts in Mathematics” course.
Summary
 “Concepts in Mathematics” class covers probability, statistics, algebra and personal finance. The class’s major
components feature: Four unit tests, online homework and quizzes, in-class participation and a multiple choice
final exam. Standard grading scale used for all assessments and for the final course grade.
 The tutorial class’s purpose was to prepare students for their “Concepts in Mathematics” coursework. The
class featured question and answer time, brief lecture and time to work on tutorial homework or “Concepts in
Mathematics” homework.
 The tutorial class contained five online unit tests and in-class participation. If students scored high enough on
the Pre-Test, they were excused from completing the remaining assignments for that unit. The standard

15
grading scale was also used for this class; however, the grade students earned in this class did not impact their
GPA.
C. Description of Statistical Tests
1. Mann-Whitney U
The Mann-Whitney U (sometimes referred to as the Wilcoxon-Mann-Whitney Test, WMW abbreviated) takes
the sample space under study and partitions it into two groups, say H (the control) and K (the experimental group) [6].
The Mann-Whitney U investigates if the distribution of H is identical to K by converting data into ranks while
maintaining group membership [17]. Larsen and Marx [14] stipulate that the probability density functions (pdfs) and
standard deviations of the two groups being compared must be the same in order to use the Mann-Whitney U Test.
The null hypothesis is and the alternative hypothesis is . Suppose two independent random
samples of sizes n and m are obtained from probability density functions , respectively. Combine the
samples together and rank the observations; note that is the rank of the i th observation. In the event of a tie,
average the ranks they would have otherwise received, if different. Now an indicator variable, , is introduced, where
if the i th observation originates from and 0 else wise. The test statistic is then defined as
∑ . The null hypothesis is rejected if where is the critical value for the WMW U distribution
[14]. This test determines if there is any gap between the two distributions; the larger the sum of the ranks, the larger
the shift between .
Why not use the t-test instead of the Mann-Whitney U Test when comparing two groups? According to Fay
and Proschan [6], the WMW test should be used for very skewed distributions and if there exists a “small possibility of
gross errors in the data” [6]. Since the author cannot validate the accuracy of all the data used in this study, a
conservative approach was applied. Furthermore, WMW better discriminates outliers than t-tests do. This is due to
the Mann-Whitney U’s high asymptotic relative efficiency (ARE) compared against the Student t-test under non-normal
populations [17].

16
2. Chi-Square
The Chi-Square statistic is calculated by ∑ where is the observed frequency of the ith
category
and is the expected value of the ith
category with being the row and column totals respectively [7].
Gingrich spells out the primary assumptions of the Chi-Square Test to be and each observation is independent
of one another [7]. The null hypothesis is no association between the two variables under study; the alternative
hypothesis states there exists an association between the two variables. The null hypothesis should be rejected if
where r and c represent the number of rows and columns present in the contingency table,
respectively [14].
3. Pearson Correlations
Correlations provide researchers with a “dimensionless measure of dependency so that one relationship can be
compared to another” with relative ease [14]. In general, this is accomplished by setting:
√
. Correlations exhibit the property | | [14]. When the moments are replaced by their
respective estimators, we arrive at the Pearson Correlation Coefficient. The Pearson correlation coefficient is given by
√
where ∑ ∑
∑ ∑
∑
∑
∑
[8]. The null hypothesis stipulates no population correlation exists ; the alternative
hypothesis states there is a population correlation .
If any relationship exists between two variables, correlations strive to demonstrate the direction, form and
strength of the relationship. Correlations do not imply causation; they simply assert the (non)existence of a
relationship between two variables. Additionally, correlations cannot be generalized beyond the scope of these
students under study. Finally, the most useful aspect of correlations is the coefficient of determination; this statistic

17
measures the variability of the first variable as explained by the second variable [8]. Outliers can dramatically affect
correlations; therefore, the zero scores were removed from the data set before the correlations were calculated.
4. Linear Regression
Larsen and Marx [14] point out four important assumptions for the linear regression model. First, | , the
pdf of Y for a given x, is normal for all x. Second, the standard deviation for | is the same for all x. Third,
| . Finally, all of the distributions are independent. Given the points adhere to
the simple linear model, | , the maximum likelihood estimators are given by [14]:
̂
∑ ∑ ∑
(∑ ) (∑ )
̂ ̅ ̂ ̅
̂ ∑( ̂)
̂ ̂ ̂
In order to discern if the linear regression model itself as a whole is significant, the F ratio of MSR to MSE is
constructed. This number is then compared to its critical value where [13]. If the
regression model survives this first step, then the coefficients of the regression model are tested. To test the
coefficients of a given regression model for significance, the null hypothesis is pitted against the
alternative hypothesis . Using the same data to form the linear regression model, we use the given t
statistic to determine if the null hypothesis should be rejected. should be rejected if | | . The hypothesis
test for is similar to that of [14].
̂
√∑ ̅⁄

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D. Statistical Testing and Analysis
For all testing and analysis, the author set alpha to be 0.05 and used SPSS Version 20 for all statistical testing.
When comparing factors outside the scope of the “Concepts of Mathematics” class, the author used Mann-Whitney U
Tests to study the two groups. Table 1 shows the only statistically distinguishable difference between those students
in the tutorial class versus those not enrolled in the tutorial class is the COMPASS algebra placement test score
(COMPASSAlg). This is reasonable because the COMPASS Algebra score prevented tutorial students from registering
for this general education mathematics class by itself instead of through this special program, thus highlighting the
primary distinction between the two groups. Tables 2 and 3 make the same comparisons as in Table 1 except using the
course section and students’ gender as the grouping variable, respectively. Tables 2 and 3 do not show any significant
difference except on the COMPASS Algebra score when students are grouped by gender. Since student ages were not
factored into this study, it is impossible to distinguish those recent high school graduates from those with previous life
experience in between high school and college. Tables 4-9 examine mean differences among components of the actual
course, grouped by tutorial class, section and gender with zero scores included in Tables 4-6 and zero scores excluded
in Tables 7-9. When the zero scores were factored out of the analysis, none of the assessments, regardless of how the
data was grouped, exhibited any significant differences. The Pre-Test tells another story altogether.
Because the author had no control over the content of the unit tests, a pre-test and post-test assessment
instrument was implemented to provide more depth to this study. All students enrolled in both sections of the
“Concepts in Mathematics” class completed the formative assessment on Midwestern Community College’s learning
management software featuring question types students would encounter during the class. The Pre-Test and Post-Test
were identical up to changes in the problem’s values and scrambled question order. The Pre-Test was administered
during Week 2 of the semester and the Post-Test was administered during Week 15. Students were given the entire
week to complete the assessment wherever they had access to the internet. To no one’s surprise, the tutorial students
scored lower overall than those not in the tutorial class on the pre-test; however, the post-test comparisons resulted in

19
no significant difference between the two groups. The Pre-Test and Post-Test were compared in a similar manner as
the unit tests.
A commonly accepted notion among the educational community is attendance is strongly related to classroom
performance. The Chi-Square Test for Independence was used to test this commonly held relationship. Attendance
rate was grouped into three categories: High (80%-100%), Average (60%-79%) and Low (0%-59%). Grades were
grouped according to the standard grading scale. The attendance rate was categorized in this manner as the mean
attendance rate was approximately 80% with a standard deviation of 20 points. Chi-Square Tests for Independence as
summarized in Tables 10-21 show attendance rate is independent of the scores students receive on all of the formal
high-stakes assessments when analyzed as a whole and by tutorial enrollment with the exception of Test 4. It is not
too surprising then to see that attendance and the final course grade are not related either.
Next, Pearson correlations were computed as a spring board for investigating additional relationships. Tables
22-25 show correlations tutorial and non-tutorial student data analyzed together and separately based on enrollment
in the tutorial class. Significant correlations are starred with one asterisk or two asterisks, 0.05 or 0.01 alpha levels
respectfully. Only notable correlations will be discussed herein. The author encountered sales personnel from ACT
proclaiming the strong connection between placement test scores and success in college level mathematics. The
COMPASS Algebra score was not significantly relatable to the final course grade. In the Chi-Square Testing for
Independence, it was noted attendance and the course grade were independent of each other; however, the
correlations suggest a significant relationship between attendance and the final course grade exclusive for the tutorial
students. Finally, the Problem and Activities Average (ProbActAvg) variable exhibited strong and significant
correlations for all formal assessments for non-tutorial students whereas ProbActAvg was not related to Test 2 for the
tutorial students.
When comparing unit test scores, final exam scores and the final course grade between those enrolled in the
tutorial class and those not enrolled in the tutorial class but in the same general education course as the tutorial
students, the normality or homogeneity assumptions of the t-tests were often violated. So, the Mann-Whitney U

20
Independent Samples Test was used because it is robust when the normality and homogeneity assumptions are not
upheld [1]. Each unit test administration produced scores of zero; therefore, each possible situation was tested: with
and without the zero scores. Tables 26-49 show the results of the Mann-Whitney U Independent Samples Test with
the test scores of zeros included and excluded, appropriately marked grouped by tutorial enrollment, section and
gender. The questions that were significantly different in the tables including test scores of zero were the same as the
tables excluding the test scores of zero. Unit Tests 2 and 3 only exhibited one question that was significantly different
between the three groups. Unit Test 4 questions did not exhibit any differences between those enrolled in the tutorial
class and those not enrolled in the tutorial class. The unit tests were departmentalized across all sections, not just
those taught by the department chair.
Finally, Midwestern College’s administrators and the author wanted to know which factors could be used to
predict the final course grade. The remaining SPSS tables show the construction of first order regression models and
their tests for significance. Ten regression models were constructed in hopes to find the best fitting model and most
practical model. The table below summarizes the models when results from tutorial students and non-tutorial
students are analyzed together.
Model Target Input Variables Significant?
1 CourseGrade NumRemedial,
NumAttempts,
NumCredits,
GPACUMFall2011
Yes 0.163
2 CourseGrade Test1 and Final Yes 0.959
3 CourseGrade Test1 Yes 0.538

21
7 CourseGrade Final Yes 0.932
8 CourseGrade COMPASSAlg No N/A
9 CourseGrade PercentPresent No N/A
10 CourseGrade Num118Attempts,
GPACUMFall2011
No N/A
Model 1: ̂ ̂
Model 2: ̂ ̂
Model 3: ̂ ̂
Model 4: ̂ ̂
Model 5: ̂ ̂
Model 6: ̂ ̂
Model 7: ̂ ̂
Last, but not least, is a summary of the pass rates. Midwestern Community College policy states that any student who
does not attend the “last academic event” (which in this case is the final exam for this class) automatically fails the
class, regardless of their previous work and score in the class. With this policy in mind, Tables 69-72 show the
distribution of final course grades by tutorial class enrollment and the inclusion or exclusion of those students who did
not attempt the final exam. Midwestern Community College considers a “D” or better to be passing for most academic
programs; however, a grade of “C” or better is needed if the student intends to transfer the class to another institution
of higher learning. For the purposes of this analysis, the investigator will consider passing to be a grade of “D” or

22
better as that is what Midwestern Community College’s success rate is measured against. When zero scores are
excluded, the pass rate of those in the tutorial class is 83.3% versus those not in the tutorial class of 78.1%. When the
zero scores are incorporated into the analysis, the pass rates are 50% and 69.44%, respectively. Several of the tutorial
students experienced “life events” that dramatically impacted their ability to perform well in class, namely
transportation, family medical emergencies and employment status changes. These reasons were verified by the
author with documentation, when possible.
The investigator created and analyzed attitude surveys for students enrolled in the tutorial class and for those
not enrolled in the tutorial class. The survey questions along with survey results can be found in the appendix.

23
CHAPTER III-CONCLUSION
A. Summary: Interpretations
Students who do not meet the stated pre-requisites for general education mathematics can be successful in
the college level coursework with the proper support structures in place. When comparing the overall unit test mean
scores of those in the tutorial class to those not in the tutorial class, there was no significant difference! Despite the
fact that a small quantity of questions from each unit test were significantly different between the tutorial and non-
tutorial students, the two sections and genders, the overall unit tests were indistinguishable between the groups. This
result is equivalent to saying students who did not meet the pre-requisites are on the same equal footing as those who
have satisfied the proper pre-requisites prior to enrollment.
Proper support structures are necessary for student success, especially for the tutorial students as evidenced
by the strong correlation between the Problems and Activities Average (which can only be completed in-class) and Unit
Tests 1, 3, 4 and the Final Exam for tutorial students. Students need to see how the mathematics taught in-class
applies to their homework and life. Unfortunately, regardless of the quality of support structures in place, students,
especially tutorial students, still must participate during class time to gain any benefits. It is not enough just to show
up to class as demonstrated by the chi-square independence tests comparing percent present versus each high-stakes
assessment. The nice aspect of this design is a student’s gender and section does not significantly impact the final
course grade.
When attempting to predict a student’s final course grade, Model 2 provides the most complete picture;
however, its fruitfulness in prediction is minimal as the final exam is the last assessment given to students before the
end of the semester. With timeliness in mind, Model 3 is the best of the group; while its value is less than stellar,
it is an early indicator of student success. If students do not perform well on the first test, they can still recover as
“Concepts in Mathematics” allows for the Final Exam score to replace the lowest test score. Models 8 and 9 are in line

24
with the previous results of this analysis: attendance alone and the placement test score do not accurately predict or
correlate to student success in this course.
Not enough students sought out the college’s free tutoring services offered to them to include into this
analysis. From personal conversations with the former director of tutoring at Midwestern College, students that
regularly attend one-on-one peer tutoring sessions earn, on average, at least one half a letter grade higher than those
that do not attend tutoring [1]. The question that naturally arises from this conclusion is why is a pre-requisite needed
for the course if the co-requisite model is successful?
B. Suggestions for Further Study
Naturally, one easy extension of this study would be to expand the population under study, thereby reducing
or eliminating the size of the study limitation this study posed. The author’s employer is currently expanding the
breadth and depth of the co-requisite model by offering more sections and investigating professional development
opportunities for more adjunct faculty to become qualified to teach the “Concepts in Mathematics” course. Academic
advisors recruit students for this program if “Concepts in Mathematics” is the appropriate course for their degree,
regardless of their prior academic background. Future studies should examine the differences in success rates and
factors that influence student success such as instructors’ pedagogical backgrounds, number of qualified tutors
employed by the college, the average amount of time spent on mathematics coursework outside of class, amount of
time spent on other coursework, number of credits students are enrolled in that given semester, number of years since
each student completed their high school degree/GED, number of hours spent working for income, how many
dependents the student is responsible for; the students’ socioeconomic status as determined by Pell grant eligibility,
employment status of the instructor with the college (~76% of our mathematics faculty are adjunct instructors),
frequency their mathematics instructor misses class meetings, and, the frequency student meets with the instructor(s)
outside of class. For this study, students who did not need or otherwise qualified for the tutorial class enrolled in the
100 level mathematics course alongside tutorial students. What if all the students in the general education level
mathematics class were tutorial students enrolled in the co-requisite program? What if the co-requisite program

25
expanded to all freshman and sophomore level classes, regardless of pre-requisite requirements of the course? If this
is to be the case, why would Midwestern Community College need a placement test (The College has an open
admissions policy with a high school diploma or acceptable GED scores requirement for admission.).
Personalized tutoring is known to be a significant factor in improving success rates in mathematics coursework
[22]. What would happen to student success rates if students enrolled in the tutorial class were required to attend at
least one hour of one-on-one tutoring per credit hour of instruction? Students might object to this proposal given their
busy schedules, rightfully so if the instructor dictated the tutoring must occur on campus. Pearson, a vendor of online
learning, started offering one-on-one online tutoring twenty-four hours a day, seven days a week to be accessed when
and where the student is ready. So long as verification of tutoring can be provided, this might be a feasible option.
There are several logistical and financial problems associated with that question; so, a more realistic research question
to propose would be what would happen if all students enrolled in the general education math class were required to
spend a pre-determined number of hours in the Math Center (a place where students can quietly work on math
homework and ask for help from tutors as needed) each week as a part of their grade? Students “do not do optional”
and simply making college resources available to students in the past has not been a successful motivator to utilize
them [21, 22]. Midwest Community College’s remedial mathematics program began requiring students to visit the
Math Center in the Fall 2012 semester as a part of their course grade. The math department witnessed some
improvement in the overall pass rates in remedial coursework; however, other significant structural changes occurred
with the remedial coursework that prevent definite correlation of required time in the Math Center and success rates.
Students enrolled in the revamped remedial coursework certainly appreciated the Math Center and its tutors2
.
The college, on a statewide level, gradually replaced the COMPASS Placement Test (produced by ACT) with the
ACCUPLACER Placement Test (produced by the College Board) starting October 2012. How does this change of
placement affect enrollment in the general education math class? At some specified point in the future, the
2
The author created and administered an attitude survey for our emporium style remedial classes. One of the questions asked
about the students’ experience in the Math Center (open computer lab with tutoring).

26
ACCUPLACER Placement Test itself will be customized to fit the needs of the college. How will the customizations
affect student placement and student success versus the “off-the-shelf” version currently employed?

27
REFERENCES
[1] Baker, L. (October 2010). Indiana Association of Developmental Educators Annual Conference. Indianapolis,
Indiana.
[2] Berryman, T. and Short, P. (2010). Leading developmental education redesign to increase student success and
reduce costs. Enrollment Management Journal: Student Access, Finance, and Success in Higher Education, 4(4),
106-114. Retrieved from Indiana State University’s Interlibrary Loan Service.
[3] Complete College America. Indiana remediation report. Retrieved from
<http://www.completecollege.org/docs/Indiana_remediation.pdf>.
[4] Complete College America. Transform Remediation: The-Co-Requisite Model. Retrieved from
<http://www.completecollege.org/docs/CCA%20Co-Req%20Model%20-
%20Transform%20Remediation%20for%20Chicago%20final(1).pdf>.
[5] Dancey, C and Dancey J. Statistics Without Maths for Psychology: Using SPSS for Windows. Page 548.
[6] Fay, M. and Proschan, M. Wilcoxon-Mann-Whitney or t-test? On assumptions for hypothesis tests and multiple
interpretations. Stat Surv. 2010 ; 4: 1–39. Retrieved from
<http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2857732/pdf/nihms-185373.pdf>.
[7] Gingrich, P. Chi-Square Tests. University of Regina. Retrieved from <http://uregina.ca/~gingrich/ch10.pdf>.
[8] Gravetter, F. and Wallnau, L. (2009). Statistics for the Behavioral Sciences. 8th
ed. Cengage: Belmont.
[9] Greenberg, W. and Williams, M. (2008). New pedagogical models for mathematics instruction. Proceedings from
Rockefeller Foundation’s Bellagio Conference, 361-371. Retrieved from Indiana State University’s Interlibrary
Loan Service.

28
[10] Ivy Tech Community College of Indiana. (2011a). Annual unduplicated headcount enrollment. Retrieved from
<http://ivytech.edu/institutional-research/enrollment/FINAL_10-11_headcount.pdf>.
[11] Ivy Tech Community College of Indiana. (2011b). Metrics & targets: accelerating greatness. Retrieved July 8,
2012 from <http://ivytech.edu/acceleratinggreatness/>.
[12] Jacobs, J. Community colleges consider math options. US News and World Report. Retrieved from
<http://www.usnews.com/education/best-colleges/articles/2012/01/27/community-colleges-consider-math-
options>.
[13] Kuter, M., Nachtsheim, C., Neter, J. and Li, W. (2005). Applied Linear Statistical Models. 5th
ed. Boston: McGraw-
Hill.
[14] Larsen, R. and Marx, M. (2006). An Introduction to Mathematical Statistics and Its Applications. 4th
ed. Upper
Saddle River: Pearson.
[15] Li, K., Uvah, J., Amin, R., Hemasinha, R.. A study of non-traditional instruction on qualitative reasoning and
problem solving in general studies mathematics courses. Journal of Mathematical Sciences and Mathematical
Education, March 2010, 37-49, 4(1). Retrieved from Dr. Uvah.
[16] Lopez, J., Permouth, S. and Keck, D. (2002). Implications of mediated instruction to remote-learning in
mathematics. American Educational Research Association. Retrieved from ERIC database.
[17] “Mann-Whitney U Test (Wilcoxon Rank-Sum Test).” Encyclopedia of Measurement and Statistics. Thousand Oaks:
Sage Publications, 2007. Credo Reference. 30 July 2010. Retrieved from
<https://login.ezproxy.lib.uwf.edu/login?url=http://www.credoreference.com.ezproxy.lib.uwf.edu/entry/sage
measure/mann_whitney_u_test_wilcoxon_rank_sum_test>.
[18] Skemp, R. Relational understanding and Instrumental understanding. Arithmetic Teacher, November 1978, 9-15.
Retrieved from Dr. Elizabeth Brown’s Middle School Mathematics Methods Class, Indiana State University.

29
[19] Soderlund, K. Ivy Tech grows to biggest state college. The Journal Gazette. Retrieved from
<http://www.journalgazette.net/apps/pbcs.dll/article?AID=/20081211/LOCAL04/812110306/1026/LOCAL04>.
[20] Stokes, K. The seven new benchmarks for funding Indiana colleges. National Public Radio. 9 December 2011
from<http://stateimpact.npr.org/indiana/2011/12/09/the-seven-new-benchmarks-for-funding-indiana-
colleges/>.
[21] The National Center for Academic Transformation. (2005). Who we are. Retrieved from
<http://thencat.org/whoweare.html>.
[22] Twigg, C. (2011). The math emporium: higher education’s silver bullet. Change: The Magazine Of Higher
Learning, May-June 2011. Retrieved from <http://www.changemag.org/Archives/Back%20Issues/2011/May-
June%202011/math-emporium-full.html>.

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APPENDIX
A. IRB Approval
Mr. Ryan Grossman February 23, 2012
8000 South Education Drive
Terre Haute, IN 47802
Dear Mr. Grossman:
The Institutional Review Board (IRB) for Human Research Participants Protection has completed its
review of your proposal titled "The Effectiveness of Concurrent Enrollment in Remedial Mathematics
and General Education Level Mathematics," as it relates to the protection of human participants used in
research, and granted approval for you to proceed with your study on 02-23-2012. As a research
investigator, please be aware of the following:
* You will immediately report to the IRB any injuries or other unanticipated problems involving
risks to human participants.
* You acknowledge and accept your responsibility for protecting the rights and welfare of human
research participants and for complying with all parts of 45 CFR Part 46, the UWF IRB Policy and
Procedures, and the decisions of the IRB. You may view these documents on the Research and
Sponsored Programs web page at http://www.research.uwf.edu/internal. You acknowledge
completion of the IRB ethical training requirements for researchers as attested in the IRB
application.
* You will ensure that legally effective informed consent is obtained and documented. If written
consent is required, the consent form must be signed by the participant or the participant's legally
authorized representative. A copy is to be given to the person signing the form and a copy kept for
your file.
* You will promptly report any proposed changes in previously approved human participant research
activities to Research and Sponsored Programs. The proposed changes will not be initiated without
IRB review and approval, except where necessary to eliminate apparent immediate hazards to the
participants.

31
* You are responsible for reporting progress of approved research to Research and Sponsored
Programs at the end of the project period 08-30-2012. If the data phase of your project
continues beyond the approved end date, you must receive an extension approval from the
IRB.
Good luck in your research endeavors. If you have any questions or need assistance, please contact
Research and Sponsored Programs at 850-857-6378 or irb@uwf.edu.
Sincerely,
Dr. Richard S. Podemski, Associate
Vice President for Research
And Dean of the Graduate School
CC: Subhash Bagui, Kuiyuan Li
Dr. Carla Thompson, Chair
IRB for the Protection of Human
Research Participants

32
B. Syllabi
MIDWESTERN COMMUNITY COLLEGE
MATH 118-00G Concepts in Mathematics
Spring 2012 Mon/Wed 10:00-11:15 Room-H102
INSTRUCTOR: Carrie McCammon OFFICE: H-116A
E-MAIL: cmccammo@midwestern.edu PHONE: (XXX) XXX-XXXX
or 1-800-XXX-XXXX ext XXXX
OFFICE HOURS: Additional times available by appointment
Monday 8:30-10:00 Thursday 10:30-12:00
Wednesday 8:30-10:00 Friday 8:30-12:00
PREREQUISITE (S): Demonstrated competency through appropriate assessment or a grade of
“C” or better in MATH 015 Fundamentals of Algebra I or MATH 023 Essentials of Algebra
I or MATH 050 Basic Algebra or MATH 080 Mathematics Principles with Algebra
PROGRAM: Liberal Arts CREDIT HOURS: 3
RESPONSIBLE DIVISION: Liberal Arts CONTACT HOURS: 48
CATALOG DESCRIPTION: Through real-world approaches, present mathematical
concepts of measurement, proportion, interest, equations, inequalities and functions, probability
and statistics. Brief survey of college mathematics.
COURSE OBJECTIVES: Upon successful completion of this course the student will be expected to:
1. Recognize proportional reasoning and solve proportion problems including both direct and inverse
variation.
2. Translate realistic problems into mathematical statements using formulas as appropriate.
3. Use function notation. Graph linear and quadratic functions by the point-plotting method.
4. Solve linear equations and inequalities in one variable.
5. Graph linear equations in two dimensions and inequalities in one dimension.
6. Calculate slope, use slope-intercept form of a line, and interpret slope as a rate of change.
7. Recognize and operate within and between different measurement systems including dimensional
analysis.
8. Solve percent problems including financial applications with simple and compound interest.

33
9. Analyze data including creating frequency distributions and calculating mean, median,
mode, range and standard deviation.
10. Recognize characteristics of a normal distribution. Calculate z-scores and percentiles.
11. Calculate probabilities, including AND, OR, NOT and conditional probability
12. Calculate and interpret expected values and weighted averages.
13. Solve counting problems using Fundamental Counting Principle, permutations and combinations.
14. Use relevant mathematical language, laws, notations and reasoning appropriately.
15. Solve a variety of real-world application problems in the above areas.
16. Use a scientific calculator proficiently as related to coursework.
17. Use computer technology, which may include the Internet, the Web, email, or computer
tutorials to enhance the course objectives.
COURSE CONTENT: Topical areas of study include
– Measurement systems Real-world applications and
problem solving Percent and proportion Simple and compound
interest
Probability and statistics Equations, inequalities and functions
TEXT/CURRICULUM MATERIALS:
REQUIRED: Blitzer, Robert. Thinking Mathematically. FIFTH edition, Prentice Hall
(If purchased through the bookstore, a student solution’s manual is included at no
additional charge).
NOTE: This is a new edition compared to previous semesters. The new edition contains
several changes. Students are encouraged to purchase the new edition. However, an
older edition would be allowed if the student purchases a new MML access code and
understands that he/she will need to use the online ebook frequently to access the new
material.
REQUIRED: access code for MyMathLab
When purchased new through the Midwestern City Midwestern Community College
bookstore the book package includes this code. Used books or books purchased
elsewhere will require that you buy the access code separately. The code is sold
individually by the Midwestern Community College bookstore as well.
REQUIRED: any brand Scientific Calculator (non-graphing)
There are many good calculators such as Texas Instruments TI-30X II S or
TI-30X Multiview. If you would like help in selecting a calculator, please
contact your instructor.
REQUIRED: Frequent use of online resources
To complete graded tasks, this course requires the use of online resources. To support
your learning, the College provides access to computers in a variety of locations.

34
ACADEMIC HONESTY STATEMENT: The College is committed to academic integrity in all
its practices. The faculty value intellectual integrity and a high standard of academic conduct.
Activities that violate academic integrity undermine the quality and diminish the value of
educational achievement.
Cheating on papers, tests or other academic works is a violation of College rules. No student
shall engage in behavior that, in the judgment of the instructor of the class, may be construed
as cheating. This may include, but is not limited to, plagiarism or other forms of academic
dishonesty such as the acquisition without permission of tests or other academic materials
and/or distribution of these materials and other academic work. This includes students who aid
and abet as well as those who attempt such behavior.
The Midwestern Community College Community College Student Handbook defines the
“Scholastic Dishonesty” policy in this way: “Any student found guilty of scholastic
dishonesty, which includes plagiarism, collusion, or cheating on any examination or test is
subject to suspension from the college.”
ADA STATEMENT: Midwestern Community College seeks to provide effective services and
accommodations for qualified individuals with documented disabilities. The goal of
Disability Support Services (DSS) is to provide opportunities for equal access in college
programs, services, and activities. DSS assists students with disabilities in achieving their
educational goals through such services as academic and career counseling, adaptive testing,
tutoring, note taking, interpreting, and test proctoring.
If you need a course accommodation because of a documented disability, you are required to
register with Disability Support Services at the beginning of the semester. You may contact
this department at 800-377-4882 ext. 2282 or 812-298-2282. If you require assistance during
an emergency evacuation, notify your instructor, immediately. Look for evacuation procedures
posted in your classrooms.
COPYRIGHT STATEMENT: Students shall adhere to the laws governing the use of
copyrighted materials. They must insure that their activities comply with fair use and in no
way infringe on the copyright or other proprietary rights of others and that the materials used
and developed at Midwestern Community College contain nothing unlawful, unethical, or
libelous, and do no constitute any violation of any right of privacy.
LIBRARY STATEMENT: The Midwestern Community College Virtual Library is available to
students on and off campus. It offers full- text journals and books and other resources essential for
course assignments. It can be accessed by going to XXXXXXXXXXXXX.
WE CARE ABOUT YOUR SUCCESS: In addition to your instructor and your classmates, there are
several ways for you to receive assistance as needed for the topics in this course:
Starfish This course is part of a student success project between our institution and Starfish
Retention Solutions. Throughout the term, you may receive emails from Starfish regarding
your course grades or academic performance. Please pay careful attention to these messages
and consider the recommended actions. These are sent to you to help you be successful! In
addition your instructor may request that you schedule an appointment through Starfish or
recommend that you contact a specific campus support resource or you may be contacted

35
directly by the staff from one of these departments. To access Starfish, login to Blackboard,
select Tools, and click on the Starfish Link. If you have any questions about Starfish, please
contact your instructor.
Online Resources (MyMathLab) MyMathLab is a website that accompanies our
textbook. Online, you will have access to an enormous wealth of information. We will use
this website to complete graded work, but you will want to use the site as a learning tool to
enhance your performance in this course.
Math & Writing Study Center At the South campus in Midwestern City, we have an
open computer classroom staffed by math instructors and tutors dedicated to students
completing math and/or writing assignments. For our class, this is a great resource because
students can use the computers to access MyMathLab and other online math resources while
trained staff is nearby to help as needed. The Math & Writing Study Center is located in room
H104. The Center is staffed Monday-Thursday 9:00am-8:00pm, Friday 9:00am-4:00pm and
Saturday 9:00am-2:00pm. For more information, stop by H104 or call (812) 298-2521.
Math Tutoring Students may also receive extra help on all course concepts from the peer
tutors in the Academic Enrichment Center located in room C114 on the South campus in
Midwestern City. Trained Midwestern Community College student tutors are available
Monday-Thursday 8:00am-8:00pm and Friday 8:00am-4:45pm. Study tables are offered for
student in MATH 118. No reservations required. Come for as long as your schedule will allow
to work on course material with students from any of 118 section while tutors are nearby to
help. For more information, stop by the AEC or call (812) 298-2389. Tutoring is available at
all Midwestern City Midwestern Community College sites as well. Inquire at your local site
or look for posted advertisements.
Tutoring via Blackboard IM (instant messaging) Online tutoring sponsored by the
Academic Enrichment Center is available through Pronto between the hours of 8:00am and
4:45pm Monday through Friday. Students can access Pronto through their class inside
Blackboard. After opening any class, go to Communications and look for the Pronto link.
Once in Pronto, look for “07 Midwestern City Ask a Tutor”.
Tutoring available through PEARSON (MyMathLab company) The Pearson Tutor
Center provides a convenient opportunity for students to speak with qualified college
mathematics and statistics instructors for valuable help during evening study hours. Once
registered, students are ready to use the service in four ways: phone, fax, email, or interactive
web. Please note that this free, helpful service is NOT affiliated with the College but rather is
a service of the textbook company. The Pearson Tutor Center is available at no additional
charge with your MyMathLab subscription. To register, contact the Tutor Center by calling 1-
800-877-3016 (5pm-12am est. Sunday-Thursday) and provide your access code, Course ID, or
valid username and password of your MyMathLab account. For more information you may
call them at toll free at 1-800-877-3016 or visit their website at
www.pearsontutorservices.com

36
CALCULATOR USE: Calculators may be used in this course, for homework and for all tests.
The math department policy declares that the following types of calculators are NOT allowed:
Graphing Calculators
Those that make noise or beep Calculators that factor
polynomials or perform measurement conversions
The calculator function on a cell phone
The calculator within any hand-held device such as a Palm or other PDA
Some topics in the course may be more challenging without the use of a scientific calculator. You
should use a calculator such as the TI-30X IIS or TI-30X Multiview, but there are many other good
options. Please ask if you have questions about using a particular calculator.
ATTENDANCE POLICY: In order to provide you with a quality education, it is important for you to
attend class regularly. Any student who has decided to not complete the course should withdraw
him/herself from the course. Students must complete this process by contacting an advisor or the Office of
Admissions.
Any student who remains enrolled will receive zero scores for any work not completed and will
also receive a final course grade based on the total points possible for the course.
Students who miss class are responsible for making up the work missed. Contact your instructor
and/or a classmate. Make arrangements to copy notes from a classmate. Stay on track with the
syllabus deadlines. Utilize tutoring resources and/or instructor office hours as needed.
LAST DATE TO WITHDRAW: Friday, April 6, 2012
METHOD (S) OF DELIVERY: Lecture
METHOD (S) OF EVALUATION: In class and out of class Activities/Homework/Quizzes, 4 Unit
Tests, and 1 Final Exam. No additional points, extra credit or bonus will be offered.
GRADING PROCESS AND SCALE:
Activity Points Each Total
4 Unit Tests 100 points each 400
Final Exam 100 points 100
MyMathLab
Homework
Average of all multiplied by
0.25 to convert % to points
25
MyMathLab Quizzes
25
Problems/Activities
50
There are 600 points possible in the course. Your final course grade will be determined using the following
scale.

37
Overall
Grading Scale (%)
Course
Grade
Total Points
Needed
90% - 100% A 537 – 600
80% - 89% B 477 – 536
70% - 79% C 417 – 476
60% - 69% D* 357 – 416
Below 60% F 0 - 356
*NOTE: A grade of C or better is required in order to transfer credits to another institution.
Also, some programs will require a grade of C or better in this course. Please contact
your advisor or the admissions office with questions about this.
GRADE RECORD: All scores will be recorded in the course’s online grade book inside Distance
Learning. You access this through Campus Connect. Click on Distance Learning and then
select this course. Inside the course, you will find the button called My Grades.
Students are responsible for tracking their progress by referring to the grade book. The end of the list
will always show you an updated average of where you stand in the course. This average only
calculates the scores that have been entered up to that time. The average is weighted correctly with the
percentages that will be used to calculate your final course grade (as shown in the table above).
Inside MyMathLab, students will have access to another grade book. The scores provided in
this location are only from the activities completed in MyMathLab. These scores will
periodically be transferred into your grade book inside the course site so that all grades can be
monitored in one location.
Please check your grade book inside Distance Learning often. This is the official grade book of
the course. Please let me know if you think something might be recorded incorrectly.
MAKE-UP AND LATE WORK POLICY: Unless ADVANCE permission has been requested
and granted, all work not completed by the deadline date and time due will be subject to the
following penalties.
MYMATHLAB ASSIGNMENTS: There are NO MAKE UPS for missed MyMathLab work. Students
who miss these assignments are encouraged to use the Study Plan area inside MyMathLab to practice
material from the missed sections. NOTE: Technology issues are NOT an excusable reason for not
submitting work.
PROBLEMS/ACTIVITIES: There are NO MAKE UPS for points missed from any assigned
in-class problems or activities. In most cases, you will not be able to make these up even with
advance permission.
UNIT TESTS: If you are not in class on test day and have not made advance arrangements,
you can take the test with a penalty. Tests may be taken up to 7 days past the deadline but
will result in a loss of 10 points for each day late (excluding Sunday). You must contact the
instructor to make arrangements for the test to be available in the campus Testing Center.

38
FINAL EXAM: There are NO MAKE UPS
Regardless of the policy above, ALL WORK must be completed by the time of the FINAL EXAM.
What is ADVANCE permission? If you have a legitimate reason to miss class, talk with your
instructor ahead of time. If your instructor agrees, he/she will work with you to negotiate a new
deadline date for that task. This process must be complete before the deadline arrives, so plan
ahead.
In the case of unforeseen emergency, you must contact your instructor as soon as
possible (use email or leave a phone message). In most cases, you will be
required to provide documentation of your emergency for your instructor to
determine if an exception to the above rules would be appropriate in that
circumstance.
HOMEWORK/QUIZZES: Work will be assigned inside MyMathLab to earn points. These
assignments will have completion deadlines that are displayed within the MyMathLab
website.
Technology issues are NOT an excusable reason for not submitting work. PLAN AHEAD.
Even though not required for a grade, students are expected to practice textbook exercises for
each section studied during the course. Since it is not possible to cover every problem type
through examples in class or during graded assignments or quizzes, completing the suggested
problems from the text is the best way to ensure that you are fully prepared for the exams.
ABOUT HOMEWORK – Some important things to know about the homework:
 Work problems from the textbook before attempting the homework online.
 You can submit answers in any order and as many times as you would like (until the deadline).
This is like having built-in extra credit since you can continue to redo homework sections
until achieving 100%
 You may print out your problems to work with them offline and then return online to answer
the questions.
 There are no time limits. The assignments can be completed at multiple times. This
means you can leave and come back as often as you would like.
 There are many ways to get help on your homework (videos, similar problems, etc). Use
these resources with caution – they are very helpful, but might make it too easy to
complete the problems without fully learning the material. Make note of when you need to
use the extra helps. These are areas that you will need to study.
 Some homework questions give hints that you will NOT see on unit exams. For
example, the homework question might tell you which formula to use.
 The online homework does NOT cover every problem type from the unit. To prepare for
the unit tests, you will still need to practice the textbook problems.

39
Follow these steps to complete a HOMEWORK assignment. Go to http://www.mymathlab.com
and log in. Once you are inside the course:
1. Click on the HOMEWORK tab.
2. Click on the assignment (the section) that you wish to do.
3. Click on the first question and it will open the assignment.
4. Complete the problem and click CHECK ANSWER.
a. If you are correct, it will proceed to the next question.
b. If you are incorrect, you will receive a message. Then you can try again.
c. After about three incorrect responses (or invalid answers), the correct answer will
be displayed. Then, you may either go to a SIMILAR EXERCISE (in order to try
to a new problem to earn the points) or you can choose NEXT EXERCISE (and
leave this problem without earning its points).
5. You may jump from one exercise to another by clicking on the numbers at the top of
your screen. On the question numbers, the red and green marks designate your missed
and correct problems.
6. To receive extra help with a problem, you can click on VIEW AN EXAMPLE or HELP
ME SOLVE THIS. Anytime you see a camera icon, you can use it to watch a video clip.
7. The SUBMIT button at the bottom is optional in the homework. Your scores
automatically go into the grade book as you work each individual problem.
ABOUT QUIZZES – Some important things to remember about the quizzes:
 Be sure to finish the textbook problems AND the MyMathLab homework (earning
100% if possible) before attempting the quizzes over those sections.
 Each quiz must be completed within 75 minutes of starting it.
 Quiz questions will be similar to the online homework. Practice how to enter answers
using the homework sections so you can answer quizzes as well.
 Unlike the homework, this time there are no help buttons as you solve the quiz problems.
 Each quiz can be taken 2 times. You are not required to redo your quiz, but it is an
optional chance to learn and to improve your grade. The highest score will count as your
quiz grade.
 Once you start a quiz, you must finish it completely or receive no points for unanswered
questions. Starting a quiz or accidentally leaving during the quiz will count as one of your
2 attempts.
 Each quiz can be reviewed after you have completed it. This means you can see the correct
answers in order to study for the retake or for the exams. Review your quizzes by going to the
Gradebook inside MyMathLab and clicking “Review” next to the quiz name.
Follow these steps to complete a QUIZ. Go to http://www.mymathlab.com and log in. Once you
are inside the course:
1. Click on the Do a Quiz tab.
2. Click on the name of the Quiz that you wish to do.
3. You will be taken to a screen reminding you of the time limit and the number of attempts you
have remaining.
To begin, click “I am ready to start”.
4. You may jump from one question to another using the buttons at the bottom. DO NOT
click the Back arrow on your Browser window. If you leave the quiz page, the software
will assume you are finished (meaning you would receive zeros for any unanswered
problems).
5. The number of questions left to answer as well as the time remaining to complete will be

40
displayed in the panel at the right hand side.
6. When you are finished with all of the questions, use the buttons at the top to go back and
review your work.
Use your time wisely and make sure that you are satisfied with your answers
7. When you are completely sure that you are finished, click SUBMIT TEST. Once you
submit, your score will appear on the screen and will also go into the grade book in
MyMathLab.
8. After you have completed a Quiz, you have the option to Review it. Anytime after taking
a quiz, you can go to your grade book inside MyMathLab and click the Review button next
to the quiz name. This allows you to see the correct answers. Point your mouse to that
answer to see a pop up containing the solution you entered for that problem.
9. You have the option to take each quiz 2 times before the deadline. Both scores will show
in your grade book, but only the higher of the two scores will be used in your grade.
MORE HOMEWORK/QUIZ INFO
Although the assignments and quizzes are excellent practice for the tests, not all of the material
covered in the
homework or quiz will appear on the tests. Additionally, not everything on the tests will have been
covered in the homework or on the quizzes. Therefore, students must practice MORE than just
these graded problems in order to be successful.
While completing your homework and quizzes, you should work all problems onto scrap
paper. Organize this work so that you have the problems as notes to use as you study for the
exams. These notes will also be helpful to you in case you want to ask a question of your
instructor during class.
Graded MyMathLab homework and quizzes are due before 11:59pm EST on the deadline date.
Technology issues are NOT an excusable reason for not submitting work. PLAN AHEAD.
PROBLEMS/ACTIVITIES: Throughout the semester, class time will be spent exploring
and investigating mathematics. Work will be completed during class and/or assigned to
be submitted by a given deadline. Sometimes quizzes or other homework will be given.
Unless otherwise announced, all problems, activities, assignments and quizzes will be
graded based on a score of 10 points each.
Since you must be in class for many of these activities, it is rare that any points due to absence
will be made up. However, your lowest three scores will be dropped. All remaining items
will be averaged together then multiplied by 0.50 to convert the percentage into points to
determine the 50 points possible out of the overall course grade.
Even if not assigned for a grade, you are required to do the suggested problems from each
section to keep up with the course work. Check your performance using the answers provided
at the back of the book.
UNIT TESTS:
Each unit test is worth 100 points toward your final course grade. In some cases, partial credit
points can be earned if the problem is not completely correct but the right procedure was
followed. In order to earn this credit you must show all of your work.
Students may use a calculator during the tests. No personal notes will be allowed during the
exam. Selected formulas, charts, and conversion tables will be supplied for you on the exam
itself. Your instructor will notify you of the information that you can expect to see on the
exam.

41
Within one week of the exam deadline, your instructor will post your score inside the official
Gradebook in Distance Learning. You will also be given the chance to review your actual
graded test. If you have any question about how your test was graded or about how many
points you earned, you MUST discuss this with your instructor at this time (or arrange an
appointment to do so). After this initial chance, your instructor has the right to decline any
requests for grade corrections.
Once your instructor has been given permission by the department to do so, your graded test
will be released for you to keep. NOTE: It is your responsibility to hold onto your graded
exam. These actual documents will be extremely useful as you study for the final exam. In the
event that you question your grade, you would be responsible for producing the actual test to
prove the correct score.
FINAL EXAM:
All students will take a final exam covering all concepts studied over the semester. This test will be
worth 100 points toward your overall grade. The final is multiple choice. After completing the
paper copy of your test, you will enter your answer choices into a computer database. This will
allow you to instantly receive your exam score.
Partial credit will NOT be given on this multiple choice exam. However, you should still clearly label
and organize your work. The paper copy of the test will be checked against the computer answers to
confirm accuracy of your grade. In the case of any technical issues or discrepancies in answers, the
paper copy will be used to determine your exam score.
Students may use a calculator during the final. No personal notes will be allowed during
the exam. The same formulas or charts that were provided during the unit tests will also be
supplied for you on the exam itself.
If it would improve your overall course grade, the final exam can be counted twice (replacing your
lowest test score). Therefore, doing well on the final can enhance your semester grade. The final
exam is NOT optional and the score on the final exam may NOT be dropped.
CLASSROOM BEHAVIOR: Our classroom should be a positive learning environment. When
we work together, we can all succeed! Therefore, behavior that infringes upon a classmate’s
ability to receive instruction will not be tolerated. Such behaviors may include (but are not
limited to) talking without permission, disrespectful comments, or inappropriate use of a
computer, cell phone, or other technology. If a classmate is disturbing your learning
opportunity, please notify the instructor.
Switch cell phones to silent mode and put them out of sight before entering the
classroom. Students should not participate in sending or receiving text messages or
participate in online activities or social media during class time. Only in an extreme
circumstance should a call or text be answered during our class time. If you have such a
situation arise that cannot wait until the end of the class, please gather your belongings and
answer your call or text AFTER leaving the room. In order to limit the distractions to your
classmates, return only at a break in the instruction.

42
Unless directly related to course activities, electronic devices should not be heard
or seen within the classroom. Many electronic gadgets can be helpful academic tools as well.
For example, devices with a calendar service can organize your deadlines. Also, there are many “Apps”
available related to our course content. However, there will rarely be a need to use such items during
class time. Unless given special permission, please use your electronics before or after class time.
CREATE YOUR MYMATHLAB ACCOUNT:
MyMathLab, CourseCompass, and MathXL are all products that work together with the same
online environment
provided by our textbook publisher. We will use these components to access resources and
complete some graded coursework. Most often, we will refer to the group of items using one
name – MyMathLab (or MML).
When you purchased your textbook from the bookstore, you received a MyMathLab access code.
This string of letters and numbers is needed only one time - the very first time that you visit the
site. During that visit you will create your own username and password that will be used for all
future visits. Students who did not purchase their textbook through the campus bookstore can
purchase access during the registration process.
Using a computer with internet access, go to: www.mymathlab.com. On the right hand side,
under STUDENTS, click the “register” button. Then follow the on screen directions. To
register, you will need:
1. The access code under the pull tab of the packet which came with your textbook
2. Our course code: mccammon28256 This is the only time you will be asked for
this code.
3. Your Email address (use one that you use regularly. It is needed when you forget
your password)
4. Midwestern Community College’s zip code: XXXXX
TECHNOLOGY NEEDS FOR USING MYMATHLAB:
Anytime you want to access MyMathLab, point your internet web browser to:
http://www.mymathlab.com/.
In order to run applications with MyMathLab, your computer must meet certain requirements
and have certain components downloaded onto it. For this reason, you may NOT be able to
access MyMathLab from every computer. For example, public computer labs often have a
block on downloading software to the machine. Please keep this in mind and plan ahead as
needed to complete your assignments during the semester. Most Midwestern Community
College computers already have these downloads completed so they are ready for your use.
When you log into MyMathLab for the first time, run the MyMathLab Browser Check to
prepare your computer. Repeat the process on all computers that you might be using during the
semester.

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